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What is HoneyHive?

HoneyHive is an observability and evaluation platform designed specifically for production AI agents. Built by a team focused on AI reliability, it solves the problem of debugging, monitoring, and improving agent behavior at scale. Core capabilities include distributed tracing with OpenTelemetry, online and offline evaluation, monitoring and alerts, experiment management, and annotation queues for human feedback. It supports over 100 LLMs and agent frameworks, making it framework-agnostic. The platform is used by teams ranging from AI startups to Fortune 500 enterprises, such as Commonwealth Bank of Australia, to ensure safe and responsible deployment of AI agents. HoneyHive unifies observability and evaluation into a continuous improvement loop, enabling teams to ship quality agents with confidence. It offers both SaaS and self-hosted deployment options with strong data isolation and security features.

AI Tool Review Summary

Performance Score

4.5/5

Content/Output Quality

High, consistent, and on-brand

Interface

Clean and minimal

AI Technology
LLMNLPObservability
Purpose of Tool

Unify observability and evaluation for production AI agents.

Compatibility

Integrates with any model, framework, or agent runtime supporting OpenTelemetry, plus 100+ LLMs and agent frameworks.

Pricing

Freemium with paid tiers

Features

Features with the highest value for users are highlighted here.

OpenTelemetry-native distributed tracing

Online evaluation with LLM-as-a-judge

Session replays and graph timeline view

Customizable alerts and drift detection

Offline experiments with regression detection

Human review queues with custom rubrics

CI/CD integration for automated testing

Virtual data planes for data isolation

How It Works

1

Instrument your agent

Add HoneyHive tracing to your agent using OpenTelemetry or one of the SDKs.

2

Monitor and evaluate

View live traces, set up online evaluations, and receive alerts on failures.

3

Run experiments

Test changes offline against curated datasets to catch regressions.

4

Iterate with feedback

Use annotation queues and human review to refine agent quality.

Who Is It For?

AI Engineers

ML Teams

Product Managers

DevOps / SRE

Enterprise Teams

Startups

Quality Assurance

Coding Agents

Data Scientists

Compliance Officers

Pricing

Free

$0/monthly
  • Up to 10k traces/month
  • Basic tracing and evaluation
  • Community support
Popular

Pro

$99/monthly
  • 100k traces/month
  • Advanced monitoring and alerts
  • Experiments and datasets
  • Email support

Enterprise

Custom/monthly
  • Unlimited traces
  • Self-hosted option
  • SSO, RBAC, audit logs
  • Dedicated support

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Pros & Cons

Pros

  • Comprehensive observability across any agent framework.
  • Enterprise-grade security with SOC 2 and HIPAA compliance.

Cons

  • May require significant setup for complex multi-agent systems.
  • Pricing details are not transparent on the website.

FAQs

Just Launched

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Release History

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Rating

5.0

Pros

Cons

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